• DocumentCode
    3781826
  • Title

    Vulnerabilities Scoring Approach for Cloud SaaS

  • Author

    Zhou Li;Cong Tang;Jianbin Hu;Zhong Chen

  • Author_Institution
    Sch. of EECS, Peking Univ., Beijing, China
  • fYear
    2015
  • Firstpage
    1339
  • Lastpage
    1347
  • Abstract
    It is known to be full of challenges to score vulnerabilities of cloud services developed by different third-party providers. Although there have been a few systems for scoring vulnerabilities (e.g., CVSS) of many existing softwares, most of them are unable to be leveraged to score vulnerabilities in cloud services, because they fail to consider some important factors located in the clouds such as business context (i.e., Dependency relationships between services). This paper presents VScorer, a novel security framework to score vulnerabilities in various cloud services based on different given requirements. By inputting concrete business context and security requirement into VScorer, cloud provider can get a ranking list of vulnerabilities in the business based on the given security requirement. Following the ranking list, cloud provider is able to patch the most critical vulnerabilities first. We developed a prototype and demonstrate VScorer can work better than current representative vulnerability scoring system CVSS.
  • Keywords
    "Security","Business","Context","Concrete","Cloud computing","Algorithm design and analysis"
  • Publisher
    ieee
  • Conference_Titel
    Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom), 2015 IEEE 12th Intl Conf on
  • Type

    conf

  • DOI
    10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.242
  • Filename
    7518421